Fast image retrieval using color-spatial information |
| |
Authors: | Beng Chin Ooi Kian-Lee Tan Tat Seng Chua Wynne Hsu |
| |
Affiliation: | (1) Department of Information Systems & Computer Science, National University of Singapore, Lower Kent Ridge Road, Singapore 119260 , SG |
| |
Abstract: | In this paper, we present an image retrieval system that employs both the color and spatial information of images to facilitate
the retrieval process. The basic unit used in our technique is a single-colored cluster, which bounds a homogeneous region of that color in an image. Two clusters from two images are similar if they are of the
same color and overlap in the image space. The number of clusters that can be extracted from an image can be very large, and
it affects the accuracy of retrieval. We study the effect of the number of clusters on retrieval effectiveness to determine
an appropriate value for “optimal' performance. To facilitate efficient retrieval, we also propose a multi-tier indexing
mechanism called the Sequenced Multi-Attribute Tree (SMAT). We implemented a two-tier SMAT, where the first layer is used to prune away clusters that are of different colors,
while the second layer discriminates clusters of different spatial locality. We conducted an experimental study on an image
database consisting of 12,000 images. Our results show the effectiveness of the proposed color-spatial approach, and the efficiency
of the proposed indexing mechanism.
Received August 1, 1997 / Accepted December 9, 1997 |
| |
Keywords: | :Single-colored cluster – Content-based retrieval – Color-spatial information – Sequenced multi-attribute tree |
本文献已被 SpringerLink 等数据库收录! |
|